University, and MOC faculty workshop for very helpful comments. The authors at various times made compensated presentations at meetings that focused on issues of national competitiveness, using the data and results presented in the enclosed paper. This work was funded in part by the World Economic Forum. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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The conceptual framework of competitiveness and clusters introduced by Michael Porter in his Competitive Advantage of Nations (Free, New York, 1990 ) remains exceptionally influential, especially among practitioners. The article discusses recent learnings about Porter's conceptual framework from practical applications and research directly driven by his work. It also outlines developments in the creation and analysis of empirical datasets and the analysis of policy processes, two main areas of current research in this field that are likely to increase in importance. The aim is to provide a coherent and current representation of key elements of the framework, while also discussing a few misperceptions about the concept present among practitioners or researchers. Copyright Springer Science + Business Media, LLC 2006competitiveness, clusters, business environment, analysis, F23, L52, O13, O57, R12,

PurposeThe purpose of this paper is to provide an analysis of regional concentration patterns within ten new European Union (EU) member states, EU10, and make comparisons with EU15 and the US economy.Design/methodology/approachIndustrial specialization and clusters are measured as employment in the intersection between a sector (three‐digit NACE data) and a particular region (NUTS 2 level), with a total of 38 sectors and 41 regions within EU10. Regional cluster size and degree of specialization is measured along 3D: absolute number of employees (>10,000 jobs is used as cut‐off for a regional cluster), degree of specialization (regional sector employment is at least two times expected levels) and degree of regional market labor dominance (>3 per cent of total employment in a particular sector). Each of these three measures of cluster size, specialization and labor market focus are classified with a “star”. The largest and most specialized clusters receive three stars.FindingsEU10 exhibits 19 three‐star regional clusters, which display high values for each of the three measured parameters. In addition, there are 92 two‐star regional clusters and 313 one‐star regional clusters. The analysis also suggests that regional concentration in EU10 is clearly lower than in the USA, and slightly lower than in the old EU member states. In a few cases – IT, biopharmaceuticals and communications equipment – where the total size of the cluster is small, and there is little historical legacy in Eastern Europe, the EU10 exhibits higher geographical concentration than EU15.Research limitations/implicationsOverall, the economies of EU10 exhibit a pattern of geographical concentration close to a random distribution, i.e. the process of regional concentration and redistribution of industry is in a very early phase. If Europe is to build a more competitive economy, industrial restructuring towards larger clusters must be allowed and pushed by policy makers both at the national and EU levels.Practical implicationsPolicymakers must be well informed about geographical concentration patterns of industry. The research offers a consistent methodology of mapping regional clusters and geographical concentration patterns across sectors.Originality/valueThis paper is the first in measuring regional concentration patterns in Europe at this fine level, and is based on a new methodology developed by Professor Michael E. Porter at Harvard University. The paper has also introduced a new method of ranking clusters according to the star model.

This paper reviews implications of recent research on competitiveness and clusters for regions and regional policy. A new framing of competitiveness clarifies the role of regions. Its empirical findings align well with the literature on drivers of regional performance, but there are opportunities for mutual learning. A step-change in the availability of data on clusters and cluster policies has enabled new research approaches. Clusters are shown to have a close association with regional economic performance and evolution. Cluster policies are largely focused on strengthening existing agglomerations, not creating new ones. The paper discussed several practical insights for regional policy makers.